About
High-achieving Computer Science student with a strong foundation in developing scalable, high-accuracy predictive models and a proven track record in Generative AI. During a Data Science internship, successfully reduced generative AI latency by 30% and automated 75% of manual pipeline work. Proficient in Python, AWS, Docker, LangChain, and CI/CD tools, eager to apply advanced ML/AI expertise to drive impactful solutions.
Work
Bangalore, Karnataka, India
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Summary
Led the deployment of AI/ML applications and optimized data pipelines, significantly enhancing predictive accuracy and operational efficiency.
Highlights
Deployed Python-based AI/ML applications, enhancing predictive accuracy by 15%.
Developed Retrieval-Augmented Generation (RAG) based GenAI applications using LangChain, reducing latency by 30%.
Systematized ML pipelines with MLflow, Airflow, and DVC, automating 75% of manual work.
Streamlined CI/CD deployment workflows on AWS using Git, Bash, and GitHub Actions.
Awards
Certificate of Recognition for Contributions as Cultural Secretary
Awarded By
Indian Institute of Information Technology Raichur
Recognized for significant contributions in the role of Cultural Secretary, demonstrating leadership and organizational skills.
First Place, Inter-IIIT Basketball Competition
Awarded By
Inter-IIIT
Awarded first place in the Inter-IIIT Basketball Competition.
Skills
Programming Languages & Libraries
Python, Pandas, Scikit-learn, Flask, SQL, Bash.
Machine Learning
Supervised Learning, Unsupervised Learning, PyTorch, TensorFlow, AWS SageMaker.
Generative AI & NLP
LangChain, Hugging Face, Prompt Engineering, RAG (Retrieval-Augmented Generation).
Data Science
Exploratory Data Analysis (EDA), Feature Engineering, Data Visualization.
MLOps & Pipelines
MLflow, Apache Airflow, DVC, CI/CD, Docker, GitHub Actions.
Tools & Platforms
Git, AWS, Grafana, Tableau, Excel, Dagshub, PowerPoint, PowerBI, S3.
Web Development
React, TypeScript, Netlify.